Functional characterization and pharmacochaperone rescue of a novel SLC6A1 variant associated with developmental epileptic encephalopathies

Abstract Mutations in SLC6A1 , encoding the γ-aminobutyric acid (GABA) transporter 1 (GAT-1), are associated with a spectrum of neurodevelopmental disorders, including epilepsy syndromes, intellectual disability (ID), and autism. An important question is whether the impact of these mutations can be predicted at scale using artificial intelligence (AI), and how such predictions correlate with experimental findings. In this study, AI was explored as a predictive tool, not as a replacement for data collected experimentally. We reported clinical presentations including seizures and EEG features, autism related phenotypes and motor skills in a novel variant c.1069G > A (p.Ala357Thr, A357T) in two siblings. We used both AI tools and experimental approaches to characterize this novel mutation in the SLC6A1 gene and compared it with another variant in the same amino acid, c.1070 C > T (p.Ala357Val, A357V). Both AI and experimental approaches indicate that the GAT-1(A357T) and (A357V) mutations destabilize the global protein conformation and have increased localization inside the endoplasmic reticulum (ER). Additionally, the presence of the mutant GAT-1 made the wildtype GAT-1 less mature. Radioactive 3 H-labeled GABA uptake assay indicated the mutation drastically reduced the function of the GAT-1(A357T) compared with the wildtype across cell types and pharmacochaperones such as 4-phenylbutyrate rescued the trafficking and function of the mutant GAT-1. Common and differential clinical phenotypes were identified in the siblings carrying the same variant. Mutant GAT-1 caused increased ER retention and impaired the trafficking of wild type GAT-1. PBA treatment rescued the mutant GAT-1 protein expression and GABA uptake function. AI-assisted in silico protein structural modeling and experimental approaches consistently suggest that the A357T and A357V variants destabilize global GAT-1 protein conformation. AI-assisted protein stability predictions provide supportive structural insight but cannot replace experimental assessment of GAT-1 expression and function.